mirror of
https://github.com/slsdetectorgroup/aare.git
synced 2026-10-23 00:31:28 +02:00
Erik Fröjdh
58da96d6f0
An unset GapPixels::module_gaps defaulted to the chip gap, so every module boundary received two extra rows or columns. Two stacked Jungfrau modules read as 1030x1030 instead of 1030x1028. Unset now means no pixels between modules; only the chip boundaries inside a module receive a gap. Also drop the explicit lambda capture in split_edge_counts that clang reported as unused for floating point pixels.
117 lines
5.2 KiB
Python
117 lines
5.2 KiB
Python
# SPDX-License-Identifier: MPL-2.0
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import numpy as np
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import pytest
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from aare import DetectorType, GapPixels, ModuleGaps, ROI, gapped_shape, insert_gap_pixels
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def reference(image, boundaries_x, boundaries_y, fill=0):
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"""Insert gap columns and rows with numpy: boundaries map a source index to
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the number of pixels inserted before it."""
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cols = [index for index, count in boundaries_x for _ in range(count)]
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rows = [index for index, count in boundaries_y for _ in range(count)]
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result = np.insert(image, cols, fill, axis=1)
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return np.insert(result, rows, fill, axis=0)
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def test_configuration_defaults_and_equality():
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gaps = GapPixels()
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assert gaps.chip_gap == 2
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assert gaps.module_gaps is None
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assert gaps.fill_value == 0
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assert gaps.split_counts is False
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assert gaps.seed is None
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assert gaps == GapPixels()
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assert gaps != GapPixels(fill_value=1)
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gaps = GapPixels(chip_gap=4, module_gaps=ModuleGaps(8, 36), fill_value=-1, split_counts=False, seed=5)
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assert gaps.module_gaps == ModuleGaps(x=8, y=36)
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assert gaps.seed == 5
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assert "ModuleGaps(x=8, y=36)" in repr(gaps)
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gaps.module_gaps = None
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assert gaps.module_gaps is None
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def test_gapped_shape():
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assert gapped_shape(ROI(0, 1024, 0, 512), DetectorType.Jungfrau) == (514, 1030)
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assert gapped_shape(ROI(0, 1024, 0, 1024), DetectorType.Jungfrau) == (1028, 1030)
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assert gapped_shape(ROI(0, 1024, 0, 1024), DetectorType.Jungfrau, GapPixels(module_gaps=ModuleGaps(8, 36))) == (1064, 1030)
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assert gapped_shape(ROI(0, 512, 0, 512), DetectorType.Eiger, quad=True) == (514, 514)
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assert gapped_shape(ROI(256, 512, 0, 256), DetectorType.Jungfrau) == (256, 256)
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assert gapped_shape(ROI(255, 257, 0, 1), DetectorType.Jungfrau) == (1, 4)
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with pytest.raises(ValueError):
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gapped_shape(ROI(0, 400, 0, 400), DetectorType.Moench)
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@pytest.mark.parametrize("dtype", [np.uint8, np.uint16, np.uint32, np.int32, np.float32, np.float64])
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def test_insert_gap_pixels_matches_numpy(dtype):
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rng = np.random.default_rng(1)
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image = rng.integers(0, 200, size=(512, 1024)).astype(dtype)
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result = insert_gap_pixels(image, DetectorType.Jungfrau, GapPixels(fill_value=3))
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expected = reference(image, [(256, 2), (512, 2), (768, 2)], [(256, 2)], fill=3)
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assert result.dtype == image.dtype
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assert result.shape == (514, 1030)
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assert (result == expected).all()
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def test_insert_gap_pixels_without_module_gaps():
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# two stacked modules: chip gaps at rows 256 and 768, none at the module
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# boundary at row 512
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image = np.arange(1024 * 1024, dtype=np.uint32).reshape(1024, 1024)
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result = insert_gap_pixels(image, DetectorType.Jungfrau)
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expected = reference(image, [(256, 2), (512, 2), (768, 2)], [(256, 2), (768, 2)])
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assert result.shape == (1028, 1030)
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assert (result == expected).all()
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def test_insert_gap_pixels_with_module_gaps():
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image = np.arange(1024 * 1024, dtype=np.uint32).reshape(1024, 1024)
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gaps = GapPixels(module_gaps=ModuleGaps(8, 36), fill_value=9)
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result = insert_gap_pixels(image, DetectorType.Jungfrau, gaps)
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expected = reference(image, [(256, 2), (512, 2), (768, 2)], [(256, 2), (512, 36), (768, 2)], fill=9)
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assert result.shape == (1064, 1030)
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assert (result == expected).all()
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def test_insert_gap_pixels_in_roi():
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image = np.array([[11, 22]], dtype=np.uint16)
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result = insert_gap_pixels(image, DetectorType.Jungfrau, roi=ROI(255, 257, 10, 11))
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assert result.tolist() == [[11, 0, 0, 22]]
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# a gap on the ROI border is not inserted
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image = np.arange(8, dtype=np.uint16).reshape(2, 4)
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result = insert_gap_pixels(image, DetectorType.Jungfrau, roi=ROI(256, 260, 0, 2))
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assert (result == image).all()
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def test_insert_gap_pixels_split_counts():
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rng = np.random.default_rng(2)
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image = rng.integers(0, 1000, size=(512, 1024)).astype(np.uint32)
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gaps = GapPixels(split_counts=True, seed=3)
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first = insert_gap_pixels(image, DetectorType.Jungfrau, gaps)
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second = insert_gap_pixels(image, DetectorType.Jungfrau, gaps)
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assert first.sum() == image.sum()
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assert (first == second).all()
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# edge pixel and its gap pixel hold floor and ceil of the half; row 255
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# is excluded because it is split again vertically
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pair = np.stack([first[:255, 255], first[:255, 256]])
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assert (pair.sum(axis=0) == image[:255, 255]).all()
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assert (pair.max(axis=0) == (image[:255, 255] + 1) // 2).all()
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halves = insert_gap_pixels(np.full((2, 2), 3.0), DetectorType.Jungfrau, gaps, roi=ROI(255, 257, 255, 257))
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assert (halves == 0.75).all()
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def test_insert_gap_pixels_rejects_bad_input():
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image = np.zeros((400, 400), dtype=np.uint16)
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with pytest.raises(ValueError):
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insert_gap_pixels(image, DetectorType.Moench)
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with pytest.raises(ValueError):
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insert_gap_pixels(image, DetectorType.Jungfrau, roi=ROI(0, 401, 0, 400))
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with pytest.raises(ValueError):
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insert_gap_pixels(np.zeros((2, 2, 2), dtype=np.uint16), DetectorType.Jungfrau)
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with pytest.raises(TypeError):
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insert_gap_pixels(np.zeros((2, 2), dtype=np.int64), DetectorType.Jungfrau)
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with pytest.raises(ValueError):
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insert_gap_pixels(image, DetectorType.Jungfrau, GapPixels(split_counts=True, chip_gap=4))
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